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Developing a resilient supply chain through supplier flexibility and reliability assessment

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  • Masoud Kamalahmadi
  • Mahour Mellat-Parast

Abstract

In this study, we examine the optimal allocation of demand across a set of suppliers in a supply chain that is exposed to supply risk and environmental risk. A two-stage mixed-integer programming model is used to develop a flexible sourcing strategy under disruptions. Our model integrates supplier selection and demand allocation with transportation channel selection and provides contingency plans to mitigate the negative impacts of disruptions and minimise total network costs. Finally, a numerical example is presented to illustrate the model and provide insights. The findings suggest that developing contingency plans using flexibility in suppliers’ production capacity is an effective strategy for firms to mitigate the severity of disruptions. We also show that flexibility and reliability of the suppliers and regions play a significant role in determining contingency plans for during disruption. Findings generally show that highly flexible suppliers receive less allocation, and their flexible capacity is reserved for disruptions. For firms that do not incorporate risk management into supplier selection and allocation, the recommendation is to source from fewer, more reliable suppliers with less risk of disruption. Our findings also emphasise that the type of disruption has important implications for supplier selection and demand allocation. This study highlights the supply chain risk management strategy of regionalising as a means for minimising the impact of environmental disruptions.

Suggested Citation

  • Masoud Kamalahmadi & Mahour Mellat-Parast, 2016. "Developing a resilient supply chain through supplier flexibility and reliability assessment," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 302-321, January.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:302-321
    DOI: 10.1080/00207543.2015.1088971
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    Cited by:

    1. Alikhani, Reza & Ranjbar, Amirhossein & Jamali, Amir & Torabi, S. Ali & Zobel, Christopher W., 2023. "Towards increasing synergistic effects of resilience strategies in supply chain network design," Omega, Elsevier, vol. 116(C).
    2. Wong, Christina W.Y. & Lirn, Taih-Cherng & Yang, Ching-Chiao & Shang, Kuo-Chung, 2020. "Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization," International Journal of Production Economics, Elsevier, vol. 226(C).
    3. López, Cristina & Ishizaka, Alessio, 2019. "A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience," Journal of Business Research, Elsevier, vol. 103(C), pages 495-507.
    4. Yılmaz, Ömer Faruk & Yeni, Fatma Betül & Gürsoy Yılmaz, Beren & Özçelik, Gökhan, 2023. "An optimization-based methodology equipped with lean tools to strengthen medical supply chain resilience during a pandemic: A case study from Turkey," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    5. Choksy, Umair Shafi & Ayaz, Muhammad & Al-Tabbaa, Omar & Parast, Mahour, 2022. "Supplier resilience under the COVID-19 crisis in apparel global value chain (GVC): The role of GVC governance and supplier’s upgrading," Journal of Business Research, Elsevier, vol. 150(C), pages 249-267.
    6. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2017. "An assessment of supply chain disruption mitigation strategies," International Journal of Production Economics, Elsevier, vol. 184(C), pages 210-230.
    7. Shekarian, Mansoor & Reza Nooraie, Seyed Vahid & Parast, Mahour Mellat, 2020. "An examination of the impact of flexibility and agility on mitigating supply chain disruptions," International Journal of Production Economics, Elsevier, vol. 220(C).
    8. Kaur, Harpreet & Prakash Singh, Surya, 2021. "Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies," International Journal of Production Economics, Elsevier, vol. 231(C).

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